Study on prediction methods for dynamic systems of nonlinear chaotic time series

DOI10.1007/BF02438202zbMath1091.93555MaRDI QIDQ2388222

Junhai Ma, Baogui Xin, Yu-Shu Chen

Publication date: 9 September 2005

Published in: Applied Mathematics and Mechanics. (English Edition) (Search for Journal in Brave)

zbMATH Keywords

parameter identificationtime series predictionwavelet neural networknonlinear self-related chaotic model

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45)

Cites Work

• Threshold value for diagnosis of chaotic nature of the data obtained in nonlinear dynamic analysis
• The influence of the different distributed phase-randomized on the experimental data obtained in dynamic analysis.
• A fundamental bias in calculating dimensions from finite data sets
• Predicting chaotic time series with wavelet networks
• Embedding as a modeling problem
• The matric algorithm of Lyapunov exponent for the experimental data obtained in dynamic analysis
• The nonlinear chaotic model reconstruction for the experimental data obtained from different dynamic system
• Detection of chaotic determinism in time series from randomly forced maps
• An analytic and application to state space reconstruction about chaotic time series
• Study on the prediction method of low-dimension time series that arise from the intrinsic nonlinear dynamics

This page was built for publication: Study on prediction methods for dynamic systems of nonlinear chaotic time series